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<div class="document">


<p class="infomark"><strong>What it does</strong></p>
<p>This program computes the q-values based on the p-values of multiple simultaneous tests. The q-values are computed using a specific R package, created by John Storey and Alan Dabney, called &quot;qvalue&quot;. The program takes five inputs:</p>
<ul class="simple">
<li>The first input is a TABULAR format file consisting of one column only that represents the p-values of multiple simultaneous tests, one line for every p-value.</li>
<li>The second input is the lambda parameter. The user can choose either the default: seq(0, 0.95, 0.05) or a decimal number between 0.0 and 1.0.</li>
<li>The third input is PI method which is either &quot;smoother&quot; or &quot;bootstrap&quot;.</li>
<li>The fourth input is the FDR (false discovery rate) level which is a decimal number between 0.0 and 1.0.</li>
<li>The fifth input is either TRUE or FALSE for the estimate robustness.</li>
</ul>
<p>The program gives two outputs:</p>
<ul class="simple">
<li>The first output is a TABULAR format file consisting of three columns:</li>
</ul>
<blockquote>
<ul class="simple">
<li>the left column represents the p-values of multiple simultaneous tests, one line for every p-value</li>
<li>the middle column represents the q-values corresponding to the p-values</li>
<li>the third column represent the significance values, either 1 for significant or 0 for non-significant</li>
</ul>
</blockquote>
<ul class="simple">
<li>The second output is a PDF format file consisting of three pages:</li>
</ul>
<blockquote>
<ul class="simple">
<li>the first page represents the p-values histogram</li>
<li>the second page represents the q-values histogram</li>
<li>the third page represents the four Q-plots as introduced in the &quot;qvalue&quot; package manual.</li>
</ul>
</blockquote>
<p><strong>Example</strong></p>
<p>Let us have the first input file of p-values as follows:</p>
<pre class="literal-block">
0.140627492
0.432249886
0.122120877
0.142010182
0.012909858
0.000142807
0.039841941
0.035173303
0.011340057
1.01E-05
0.212738282
0.091256284
0.547375415
0.189589833
6.18E-12
0.001235875
1.10E-05
9.75E-07
2.13E-18
2.54E-16
1.20E-19
9.76E-14
0.359181534
0.03661672
0.400459987
0.387436466
0.342075061
0.904129283
0.031152635
</pre>
<p>Running the program will give the following output:</p>
<pre class="literal-block">
pi0: 0.140311054

FDR level: 0.05

p-value         q-value         significant
0.1406275       0.02889212      1
0.4322499       0.06514199      0
0.1221209       0.02760624      1
0.1420102       0.02889212      1
0.01290986      0.00437754      1
0.000142807     6.46E-05        1
0.03984194      0.01013235      1
0.0351733       0.009932946     1
0.01134006      0.004194811     1
1.01E-05        5.59E-06        1
0.2127383       0.03934711      1
0.09125628      0.02184257      1
0.5473754       0.07954578      0
0.1895898       0.03673547      1
6.18E-12        5.03E-12        1
0.001235875     0.00050288      1
1.10E-05        5.59E-06        1
9.75E-07        6.61E-07        1
2.13E-18        4.33E-18        1
2.54E-16        3.45E-16        1
1.20E-19        4.88E-19        1
9.76E-14        9.93E-14        1
0.3591815       0.06089654      0
0.03661672      0.009932946     1
0.40046 0.0626723       0
0.3874365       0.0626723       0
0.3420751       0.06051785      0
0.9041293       0.1268593       0
0.03115264      0.009750824     1
</pre>
<img alt="p_hist.png" src="p_hist.png" />
<img alt="q_hist.png" src="q_hist.png" />
<img alt="Q_plots.png" src="Q_plots.png" />
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